Estimation of parameters of Kumaraswamy-exponential distribution based on adaptive type-II progressive censored schemes

Abstract

In this paper, we consider estimation of parameters for a two-parameter Kumaraswamy-exponential distribution based on adaptive type-II progressive censoring schemes which is a mixture of type-I and progressive type-II censoring schemes. The maximum likelihood estimators of the parameters are obtained. Bayes estimators are also obtained using different loss functions such as squared error loss function, LINEX loss function, and entropy loss function. For Bayes estimation, we use the importance sampling method. A simulation study is then performed for comparing various estimators developed in this paper. All Bayesian estimates are compared with the corresponding maximum likelihood estimates numerically in terms of their bias and mean square error values and found that Bayes estimators perform better than MLEs for α and β. A real data set is also used for illustration.